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arXiv · 1506.00468

Classifying Tweet Level Judgements of Rumours in Social Media

Michal Lukasik·Trevor Cohn·Kalina Bontcheva
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Abstract

Social media is a rich source of rumours and corresponding community reactions. Rumours reflect different characteristics, some shared and some individual. We formulate the problem of classifying tweet level judgements of rumours as a supervised learning task. Both supervised and unsupervised domain adaptation are considered, in which tweets from a rumour are classified on the basis of other annotated rumours. We demonstrate how multi-task learning helps achieve good results on rumours from the 2011 England riots.

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Michal Lukasik, Trevor Cohn, Kalina Bontcheva. 2015-09-10. Classifying Tweet Level Judgements of Rumours in Social Media. https://arxiv.org/abs/1506.00468

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